Terahertz (THz) absorbers are attractive for emerging 6G links, imaging, sensing and electromagnetic protection; however, practical devices often face coupled trade-offs among absorption bandwidth, structural complexity, polarization/angle robustness and active tunability. Here, a dual-functional-layer metamaterial absorber is proposed. Unlike conventional single-layered designs, the synergy between a periodically patterned VO2 layer and a continuous VO2 film forms an asymmetric Fabry-Pérot (F-P) cavity that reconfigures the internal field distribution across different phase states. This design allows a continuous VO2 film and a periodically patterned c layer to form an asymmetric F-P cavity, while a metallic backplane eliminates transmission. Finite-element simulations are carried out from 0.1 to 20 THz, and the conductivity evolution across the VO2 insulator-to-metal transition is described with a Drude model. When both VO2 layers are in the metallic state, the absorber provides ultrabroadband near-perfect absorption, exhibiting absorptance above 90% from 3.25-16.56 THz with an average absorptance of approximately 96.4%. By programming the phase states of the two VO2 layers, the response can be switched among an ultrabroadband mode, a dual-band mode (2.15-6.17 THz and 11.75-16.52 THz), and a narrowband mode with a peak absorptance of about 99.98%. The design is essentially polarization-insensitive for rotation angles from 0° to 90° and preserves high absorption up to 60° incidence under both TE and TM polarizations. These results demonstrate a compact route to multifunctional THz absorbers combining ultrabroad bandwidth, wide-angle robustness and reconfigurable control for adaptive THz systems.
Prism-coupled layered structures, including surface plasmon resonance (SPR) sensors and resonant mirror (RM) sensors, have been widely used in refractive index sensing. However, the interference-based signal detection of RM is sophisticated, and the low quality factor of the SPR mode limits sensing performance. In this work, an absorptive RM with independently tunable radiative and absorptive losses is proposed and theoretically investigated. By controlling the buffer layer thickness and waveguide extinction coefficient separately, the radiative quality factor (Qr) and absorptive quality factor (Qa) can be adjusted without crosstalk. When Qr and Qa are matched at the critical coupling condition, perfect absorption with ultra-narrow bandwidth is achieved. With a simple layer stack and compatibility with existing prism-coupled schemes, the proposed absorptive RM may offer a promising platform for label-free sensing.
Efficient electromagnetic absorption is essential for optical modulation and integrated photonic devices and can be significantly enhanced by interference-assisted resonant nanostructures. Here, we propose a borophene-dielectric nanostructure operating at telecommunication wavelengths to realize tunable coherent perfect absorption (CPA). The structure supports guided-mode resonances (GMRs), which generate strong near-field enhancement near the borophene layer and promote efficient light-matter interaction. Under single-port excitation, resonance-enhanced absorption with directional asymmetry is observed, yielding peak absorption of 42.5% and 57.4% for opposite incidence directions. Under dual-port coherent excitation, CPA with a narrow bandwidth of 0.82 nm occurs at 1549.8 nm when the scattering matrix satisfies the zero-determinant condition. At the CPA wavelength, the absorption can be continuously tuned from below 10% to above 99.9% by adjusting the phase difference between the two incident beams. Electrical tuning of the borophene carrier concentration further enables a resonance shift of 12.4 nm while maintaining absorption above 95%, nearly fifteen times larger than the intrinsic CPA resonance linewidth. Structural asymmetry further leads to unequal external coupling strengths, enabling asymmetric interferometric light-light control under unequal-intensity excitation. These results demonstrate a compact platform for phase-controlled absorption and coherent optical switching in integrated photonic systems.
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The selective catalytic conversion of biomass-derived 5-hydroxymethylfurfural (HMF) into high-value chemicals represents a critical pathway toward sustainable chemical synthesis and carbon neutrality. However, precise control over the oxidation degree to avoid over-oxidation to CO2 remains a formidable challenge. Herein, we report a two-dimensional (2D) Fe-MoS2 catalyst that enables highly selective electrooxidation of HMF to formic acid (FA) with near-complete carbon retention. Leveraging the unique electronic structure of the MoS2 substrate, the Fe-MoS2 catalyst achieves a FA yield of 86% and a Faradaic efficiency of 95% at an applied potential of 1.52 V vs. RHE, alongside excellent cycling stability and a nearly 100% carbon balance. Mechanistic investigations reveal that the high work function and suitable valence band position of Fe-MoS2 create an electron-rich interface that stabilizes carboxylic acid intermediates, while its large specific surface area and mesoporous architecture physically suppress over-oxidation. Density functional theory (DFT) calculations further demonstrate a lower energy barrier for FA stabilization, promoting selective oxidative bond cleavage. This work highlights the critical role of modulating catalytic selectivity for providing 100% carbon balance in biomass valorization.
We assessed the value of using a size ratio of implanted valve opening diameter to native annular diameter to determine postoperative hemodynamics and survival after surgical aortic valve replacement. In total, 1519 patients from 3 trials had a preoperative computed tomography scan. A size ratio was created using the implanted valve's Ebels' prosthetic valve-derived effective diameter (ED) and the patient's computed tomography perimeter-derived native annular diameter (CTD). Restricted cubic spline curves showed the association between size ratio and hemodynamic performance. Patients were divided into 3 ratio groups: <80%, 80% to 90%, and >90%. Hemodynamic performance was evaluated yearly for 5 years. Multivariable proportional hazard regression examined the association between size ratio and 5-year survival. Mean valve gradient, peak velocity, effective orifice area (EOA), indexed EOA, dimensionless velocity index, and prosthesis-patient mismatch were significantly better advancing from the 80% to the 90% groups (P < .001). The >90% group had a single-digit mean valve gradient, peak velocity ≤2.0 m/s, EOA ≥2.0 cm2, indexed EOA ≥1.0 cm2/m2, dimensionless velocity index ≥0.5, and no prosthesis-patient mismatch ≥85% at 1 and 5 years. Size ratio was an independent predictor of mortality with survival benefit through 5 years (80%-90% vs <80%, hazard ratio, 0.752; 95% confidence interval, 0.611-0.927, P = .008; >90% vs <80%, hazard ratio, 0.712; 95% confidence interval, 0.506-1.001, P = .05). An ED/CTD size ratio >90% is associated with optimal postoperative hemodynamic performance and improved 5-year survival. Preoperative ED/CTD ratio provides the ideal implanted valve size and helps determine if annular enlargement is necessary.
Accurate detection of Erosive Tooth Wear (ETW) is essential for early intervention and monitoring. The Basic Erosive Wear Examination (BEWE) is frequently used clinically, yet reproducibility is limited. Digital intraoral scans and Artificial Intelligence (AI) may offer increased sensitivity, reduced bias, and improved diagnostic reliability. This cross-sectional clinical study (ISRCTN16797270) recruited 61 dentate adults with mild, moderate and severe ETW, with analysis of 1,600 teeth (4,797 surfaces). Participants received a clinical BEWE and dentine-exposure examination by Examiner 1, followed by an intraoral scan (TRIOS 5, 3Shape A/S, Denmark). After a 2-week washout, Examiner 1, Examiner 2 and an AI assessment tool independently assessed BEWE and dentine on each scan. Twelve patients (n=24 scans) reflecting mild, moderate and severe wear were reassessed by Examiners and the AI to determine intra-examiner repeatability. Sensitivity, specificity, and Intraclass Correlation Coefficients (ICC) were calculated at surface, tooth and patient-level. On-scan assessments recorded increased BEWE scores >2 (37%) than clinical examination (22.3%). On-scan assessment-clinical agreement was good (ICC 0.73-0.78). AI-clinical agreement was moderate at surface level with the AI scoring more wear than clinical examination (ICC=0.65). Tooth-level sensitivity/specificity of on-scan versus clinical scoring was 0.98/0.56 respectively. AI-clinical sensitivity/specificity was 0.85/0.68. For dentine-exposure detection, sensitivity/specificity exceeded 0.80; AI achieved 0.82/0.90. Intra-examiner and inter-examiner ICC's were 0.73-0.78 and 0.49 respectively while AI demonstrated perfect repeatability (ICC=1.00). AI-derived assessments demonstrated perfect repeatability alongside comparable sensitivity/specificity with clinical assessment and improved dentine exposure assessment. Digital and AI-derived wear assessments represent promising adjuncts for earlier diagnosis and improved monitoring of ETW.
A two-warehouse inventory model is introduced with the manufacturer and retailer. They both use two warehouses for storing and selling products, with their own and a rental warehouse. The manufacturer produces both perfect and imperfect products. Defective products returned from the retailer are sent for remanufacturing. All remanufacturing products are shifted to the secondary retail stores. Every product has a lifespan, and to reduce deterioration, the manufacturer and the retailer invest in preservation technology. Both players offer trade credits to their customers. To achieve environmental sustainability, both the manufacturer and the retailer calculate and pay for their carbon emissions. The retailer advertises products in the market, as advertising policy is a significant policy for enhancing any business by attracting customers. A sustainable supply chain management model is developed to optimize the production rate, remanufacturing rate, and cycle time. A numerical experiment is performed to validate the study, and a sensitivity analysis is conducted to provide insights to managers. From numerical findings, if the holding cost increases to 20%, the profit decreases to 0.03%. The numerical results indicate the importance of remanufacturing, carbon emissions, and product quality control within a sustainable supply chain.
Accurate assessment of burn depth and total body surface area (TBSA) is critical for clinical decision-making; however, it remains subjective and prone to interobserver variability. Multimodal large language models (MLLMs) are increasingly encountered in clinical contexts, but whether these systems can reliably assess burn images remains unclear. We evaluated four MLLMs (GPT-5.4 Pro, Grok 4.1, Gemini 3.1 Pro, and Claude Opus 4.6) on 50 clinical burn photographs using a repeated-inference design with five independent runs per model. Burn depth classification was assessed in numeric and text-based formats, alongside ordinal TBSA estimation. Performance varied across the models, with burn depth accuracy ranging from 34.0 ± 6.5% to 76.4 ± 6.8% and TBSA accuracy from 32.8 ± 9.4% to 68.4 ± 3.3%. Inter-run reliability (Fleiss' κ) ranged from slight (κ = 0.171) to almost perfect (κ = 0.916), demonstrating response variability not captured by single-query evaluations. Notably, no model combined high accuracy and high reliability, indicating a dissociation between performance and consistency. All models showed a tendency toward overestimation of burn depth, including assignment of fourth-degree burns despite their absence in the dataset. Error direction analysis revealed model-specific and task-dependent biases, including opposing patterns within the same model. Internal consistency between numeric and text classifications was near-perfect (99.6-100%), indicating format-invariant but systematically biased outputs. These findings demonstrate that MLLM performance is characterized by stochastic response instability invisible to single-query evaluations. Such inconsistency for identical inputs represents a fundamental limitation for workflows requiring consistent outputs across repeated evaluations.
New food databases increasingly provide biochemical information not yet captured in standard food composition databases (FCDs). To enable precision nutrition, new methods are needed to map foods to these FCDs. We sought to provide real-world ground truth (benchmark) datasets and evaluate the use of large language models (LLMs) to match foods reported in dietary data with foods in FCDs. Two ground truth (benchmark) datasets were developed. ASA24-to-FooDB included a large FCD (9,910 entries) with many similar or perfect matches. NHANES-to-DFG2 included a small FCD (256 entries) with imperfect matches or "No Match" (46.9%). Matching methods tested included fuzzy matching, TF-IDF, semantic embedding, and LLMs. Food text description mapping using similarity scores from semantic embedding performed better on both ground truth datasets (87.8% accuracy, ASA24-to-FooDB; 48.0% accuracy, NHANES-to-DFG2) than fuzzy matching or TF-IDF. LLMs performed worse on ASA24-to-FooDB when given the entire FCD, but better on NHANES-to-DFG2 (62.6% accuracy). For foods where a correct match exists, semantic similarity yielded top K accuracies of 85% at k=5, 95% at k=10 for ASA24-to-FooDB and 96% at k=5, 98% at k=10 for NHANES-to-DFG2. A hybrid approach using semantic embeddings to select the top K matches to prompt LLMs yielded overall accuracies of 90.7% on ASA24-to-FooDB and 65.4% on NHANES-to-DFG2. An investigation of different prompt strategies and model sizes demonstrated that simpler prompts worked better for larger LLMs while smaller LLMs needed detailed instructions. To assist nutrition scientists, the best strategy (semantic mapping + LLM reranking) was implemented in an application: FoodMapper (https://foodmapper.app/). To match food text descriptions to FCDs, identifying top matches using semantic similarity followed by an LLM to choose from among those matches or "no match" resulted in the highest accuracy. FoodMapper provides users with the best solution in a user-friendly interface that facilitates manual review.
Rolling circle amplification (RCA) is a powerful isothermal nucleic acid amplification technique, yet its specificity is often compromised because padlock probes can be circularized even with imperfectly matched targets, leading to false-positive signals. Herein, we report a strand displacement-assisted FEN1 cleavage strategy to substantially improve the specificity of RCA. A dumbbell-shaped padlock probe is designed to generate dual 5' flaps only upon perfect hybridization with the target. Flap endonuclease 1 (FEN1) specifically recognizes the three-base overlap structure and cleaves the 5' flaps, enabling stringent single-base mismatch discrimination over a recognition length exceeding 23 base pairs. After FEN1 cleavage, the padlock is circularized by T4 DNA ligase, followed by RCA triggered by primer-conjugated magnetic beads. The RCA products form G-quadruplex structures that bind thioflavin T (ThT) for fluorescence readout. The method achieves excellent sensitivity for breast cancer-related biomarkers, with detection limits of 0.61 fM for hsa-miR-2682 and 1.13 fM for hsa_circ_0131242, along with high specificity (single-base resolution), good reproducibility (CV < 5%), and satisfactory recovery (95.1-101.5%) in serum. Clinical validation using 15 breast cancer patient samples and 15 healthy controls shows that the method reliably recapitulates differential expression of hsa_circ_0131242, with results highly consistent with RT-qPCR. By overcoming the inherent specificity limitation of conventional RCA, this FEN1-assisted, strand displacement-enhanced strategy provides a sensitive, reliable, and versatile platform for RNA biomarker analysis, holding great promise for early diagnosis of breast cancer and other diseases.
Congenital umbilical anomalies (umbilical cord hernia, larger umbilical hernias, and epithelialized omphaloceles) present a significant challenge for surgeons in achieving perfect reconstruction. About 10 years ago, we came up with the idea of forming six cutaneous flaps for reconstruction, resulting in what can be described as the perfect umbilicus. We demonstrate the application of this technique in three different cases of umbilical anomalies. The described technique for forming a neo-umbilicus using six cutaneous flaps is very simple and precise. Its application achieves excellent esthetic results without complications.
To evaluate the agreement and diagnostic performance of the Node Reporting and Data System 1.0 (Node-RADS) for preoperative lymph node staging in cervical cancer across readers with different experience levels. This retrospective study enrolled 439 consecutive cervical cancer patients who underwent preoperative MRI and lymph node dissection. Target nodes were pre-specified by a most experienced consultant radiologist to unify the assessment objects. Four readers (two senior with 9-11 years of experience, two junior with 3-5 years of experience) independently assigned Node-RADS scores, blinded to histopathology. Inter-reader agreement and between-group agreement were assessed using weighted and Cohen's kappa. Diagnostic performance was evaluated against histopathology as reference standard. Senior readers achieved near-perfect agreement for Node-RADS scores (k = 0.988), nodal status (k = 0.959) and all individual morphological parameters (k = 0.847-0.967). Junior readers showed moderate to substantial agreement (k = 0.554-0.754). Although junior readers requiring consensus more frequently (7.1% vs. 1.4%, p < 0.01), the between-group agreement for nodal status was substantial (k = 0.783). For nodal metastasis detection, senior readers demonstrated higher diagnostic performance (AUC 0.868; sensitivity 76.4%; specificity 97.3%) compared to junior readers (AUC 0.758; sensitivity 54.6%; specificity 97.0%), and both groups presented favorable diagnostic efficacy overall. Inter-reader agreement for nodal status was almost perfect among senior readers and substantial among junior readers. Diagnostic performance was slightly better in the senior group, suggesting an influence of reader experience.
Lapping the surfaces of Si(111) crystals in a double-crystal monochromator (DCM) has recently been shown to increase the 100 keV X-ray beam intensity by nearly an order of magnitude, raising the need for a reliable experimental evaluation of the resulting beam quality, particularly wavelength spread (energy bandwidth) and angular divergence. To address this need, a method for determining the wavelength-angle distribution of high-energy X-ray beams is developed by interpreting rocking-curve measurements as projections in wavelength-angle (DuMond) space and reconstructing the distribution using an iterative computed-tomography approach. When applied to beams produced with polished and lapped Si(111) DCMs, the method reproduces the DuMond prediction for perfect crystals and reveals systematic changes in wavelength spread while the angular divergence remains nearly unchanged. These results demonstrate a practical framework for experimentally characterizing the wavelength-angle distributions of high-energy X-ray beams, providing a basis for understanding and optimizing beam properties beyond conventional one-dimensional metrics.
It is essential for the clinical diagnosis and treatment of idiopathic membranous nephropathy (IMN) to achieve the sensitive and efficient detection of anti-phospholipase A2 receptor (PLA2R) antibodies which has been identified as a major autoantibody for IMN. In this work, we developed a multi-composite surface enhanced Raman scattering (SERS) substrate by decorating two-dimensional black phosphorus nanosheets (BP NSs) onto carbon paper (CP) through hydrothermal reaction and then triggering in-situ reduction of silver nanoparticles (Ag NPs). Except for the promising target enrichment efficiency attributed to the one-dimensional fibrous structure of CP with large specific surface area, the resulting CP@BP@Ag composite substrate exhibited perfect SERS activity owing to the synergistic effect of plasmonic coupling and charge transfer (CT). Furthermore, this triple nanoplatform was employed as immunosubstrate to detect anti-PLA2R antibodies based on a sandwich immunostructure with the participation of anti-human IgG antibodies-conjugated Raman immunoprobe. Benefiting from mature antigen-antibodies specific recognition, the limit of detection (LOD) was measured at 0.43 ng/mL. Especially, the proposed SERS-based immunoassay strategy was conducted to monitor real IMN samples, demonstrating consistent trend with the clinical method. Overall, this platform paves the way for ultrasensitive diagnostics of IMN, which offers a promising strategy for extended monitoring of renal biomarkers.
To determine whether treatment decision-making in acromioclavicular joint injuries is possible using only Alexander views with diagnostic reliability comparable to conventional pre-operative imaging. Patients with acute first-time acromioclavicular joint injuries (Rockwood II-V) at 2 specialized centers (January 2019-June 2024) were retrospectively reviewed. Inclusion required complete pre-operative imaging consisting of either a panoramic view or bilateral Zanca views, plus at least one pre-operative modified Alexander stress view. A reference classification was established using coracoclavicular distance measurements, supplemented by the modified Alexander projection. Patients were stratified into a nonoperative group (Rockwood II-IIIA) and a potentially operative group (Rockwood IIIB-V). Modified circle measurements were performed for Alexander views. Three independent surgeons first assessed all cases using anteroposterior radiographs plus Alexander view and again after a 2-week washout period using only the Alexander view and recommended operative or nonoperative treatment. Inter-rater and intrarater reliability, diagnostic accuracy relative to the reference classification, and the correlation between circles values and injury severity were calculated. Receiver operating characteristic analyses were conducted to determine cutoff values for distinguishing higher-grade injuries. 54 patients met inclusion criteria. Using complete imaging, raters demonstrated a sensitivity of 95.1% and specificity of 90.1% for treatment allocation with substantial inter-rater agreement (κ = 0.653). Using only Alexander views, diagnostic performance remained high (sensitivity 87.7%, specificity 90.1%) with substantial inter-rater (κ = 0.753) and substantial to almost perfect intrarater reliability (κ = 0.779-0.852). Modified circles values correlated strongly with injury severity (τ = 0.753, P < .001). An 18-mm threshold differentiated Rockwood IIIB from V injuries with high sensitivity (92.9%) and negative predictive value (97.2%). The Alexander view alone enabled accurate identification of high-grade instability as defined by Rockwood's classification and supported treatment decisions comparable to standard anteroposterior imaging. These findings suggest that routine panorama or Zanca views may not be required for decision-making in acute AC joint injuries.
Many hospitals perform both axial fast spin-echo T2-weighted image (FSE T2WI) and axial gradient recalled echo T2-weighted (GRE) imaging. This study was performed to compare inter-reader agreement of cervical central spinal stenosis (CCSS) grading with the use of axial GRE imaging and axial FSE T2WI. We also compared the correlations between each radiologic grade and clinical manifestations. A total of 143 patients (M: F = 71:72; mean age, 52 years) who underwent magnetic resonance imaging of the cervical spine at our hospital were included. Two radiologists evaluated the degree of CCSS from the level of C2-3 to the level of C6-7 using axial GRE imaging, axial FSE T2WI, axial GRE imaging with sagittal T2WI, and axial FSE T2WI with sagittal T2WI. Kappa statistics were used to analyze the inter-reader agreement. The existence of substantial agreement between GRE axial and FSE T2 axial images was reported by both readers (0.657 ≤ κ ≤ 0.665), who also reported almost-perfect agreement between GRE axial + T2 sagittal and T2 axial + T2 sagittal imaging (0.958 ≤ κ ≤ 0.979). The GRE axial, GRE axial + T2 sagittal, and T2 axial + T2 sagittal images showed superior correlation (moderate) compared to that of T2 axial images only (weak) in revealing the correlation between Kang grade and clinical manifestation. The agreement of CCSS grading with axial GRE imaging and axial FSE T2WI findings was substantial. Using axial GRE images led to a superior correlation between magnetic resonance sequence and clinical manifestations relative to using axial FSE T2WI.
To evaluate hydrogen peroxide (HP) permeability into the pulp chamber, objective color change, and enamel surface morphology after overnight use of over-the-counter (OTC) whitening pens. Fifty sound premolars were assigned to five groups (n = 10): control, Optic White Pen LED (OW), Colgate Luminous White Whitening Pen (LW), Equate Teeth Whitening Kit (EQ), and Whiteness Perfect 10% (WP). Fifteen molars were used for enamel surface analyses (microhardness and roughness). Products were applied for 8 h/day for 10 days. HP penetration (μg/mL) and color change (ΔEab, ΔE00, and WID) were measured by spectrophotometer. Initial HP concentration and pH were determined by titration and pH meter. Data were analyzed using ANOVA (α = 0.05). EQ showed the highest HP concentration and the lowest pH. HP penetration was significantly higher for EQ and lowest for WP (p < 0.05). No significant differences in ΔEab and ΔE00 were observed among products, while WID increased over time in all groups. Enamel surface changes were similar, except for EQ, which showed reduced microhardness (p < 0.05). Overnight OTC whitening pens showed comparable cumulative bleaching efficacy. However, EQ resulted in greater pulpal HP penetration and enamel softening. Prolonged overnight OTC whitening pen use may increase pulpal exposure and enamel softening risk, reinforcing cautious use and professional supervision.
Population cancer screening detects the presence of early-stage disease rather than assessing future disease risk. We evaluated whether widely implemented cardiovascular disease (CVD) risk models can predict 10-year cancer risk, comparing them with the QCancer risk model. We evaluated four CVD prediction models: QRISK3, the Pooled Cohort Equations (PCE), SCORE2 and SCORE2-OP. The models were recalibrated using 20% of the UK Biobank (UKB) cohort and tested in the remainder and in the Clinical Practice Research Datalink (CPRD). We gauged model performance by discrimination (c-statistics) and calibration (slope and intercept) and evaluated feature importance. In the UKB test set, the c-statistics for incident CVD ranged from 0.71 to 0.74 (9,712 events). All CVD models achieved a c-statistic of 0.63 for any cancer (23,010 events) and showed CVD-equivalent discrimination for gastro-oesophageal, liver and biliary tree, laryngeal, renal tract, and lung cancers (c-statistic range: 0.70;0.81). The recalibrated CVD models showed near-perfect calibration (median intercept 0.01, Q1;Q3 -0.05;0.03 and slope 1.01, Q1;Q3 0.95;1.14). Performance in CPRD (393,622 cancer events) was similar: the median c-statistic, calibration intercept, and slope were 0.01 (95%CI 0.00;0.02), 0.09 (95%CI 0.03;0.20), and 0.04 (95%CI 0.01;0.14) higher, respectively, in CPRD than in UKB. After age, smoking status and systolic blood pressure were the most influential predictors of cancer risk. Widely implemented CVD prediction models perform similarly to the less widely used QCancer models in the prediction of incident cancers. They may be used to inform cancer prevention and guide risk-stratified monitoring. The recalibrated models are available through an open source web application.
Adamussium colbecki is an ecologically important species (class Bivalvia) endemic to the Southern Ocean, but genomic resource for this species has remained yet limited. In this study, we first report the complete and annotated mitochondrial genome of A. colbecki, assembled using MGI paired-end sequencing. The circular mitogenome was 15,269 bp in length and comprised of 12 protein-coding genes (PCGs), two rRNA genes, and 18 tRNAs, with the atp8 gene absent, as commonly observed in bivalve molluscs. Phylogenetic analysis based on 11 mitochondrial PCGs (7,053 bp) revealed that A. colbecki formed a distinct and well-supported lineage within Pectinidae, the most closely related to Placopecten magellanicus. The 12S and 16S rRNA regions of the mitogenome were analyzed as mitochondrial DNA markers. In addition, using whole nuclear genomic information 144,512 perfect microsatellite loci (SSRs) were identified, and 30 primer-pairs were designed, among which seven polymorphic markers were developed. We then tested for their applicability to population genetics analysis and found that they were relatively highly polymorphic. These newly generated genomic resources will provide versatile genetic markers for future studies on population structure, genetic diversity, and evolutionary (demographic) history of A. colbecki, contributing to long-term population monitoring and conservation in the Antarctic marine ecosystem.